注意这里的读取 image_raw_data = tf.gfile.FastGFile("./datasets/cat.jpg", "rb").read(), 写入 f = tf.gfile.GFile("output.png", "wb") 所用的函数, 注意这里及以下都是调用的 tf.image.
- import matplotlib.pyplot as plt
- import tensorflow as tf
- image_raw_data = tf.gfile.FastGFile("./datasets/cat.jpg", "rb").read()
- f = tf.gfile.GFile("output.png", "wb")
- with tf.Session() as sess:
- img_data = tf.image.decode_jpeg(image_raw_data)
- fig = plt.figure()
- plt.imshow(sess.run(img_data))
- encoded_image = tf.image.encode_jpeg(img_data)
- f.write(encoded_image.eval())
重新调整图片大小 API
- image_float = tf.image.convert_image_dtype(img_data, tf.float32)
- resized = tf.image.resize_images(image_float, [300, 300], method=0)
裁剪或填充图片
- croped = tf.image.resize_image_with_crop_or_pad(img_data, 1000, 1000)
- padded = tf.image.resize_image_with_crop_or_pad(img_data, 3000, 3000)
截取中间 50% 的图片
central_cropped = tf.image.central_crop(img_data, 0.5)
翻转图片
transposed = tf.image.transpose_image(img_data)
处理标注框
图像的裁剪区域必须包含所提供的任意一个边界框的至少 min_object_covered 的内容.
- import matplotlib.pyplot as plt
- import tensorflow as tf
- image_raw_data = tf.gfile.FastGFile("./datasets/cat.jpg", "rb").read()
- with tf.Session() as sess:
- boxes = tf.constant([[[0.05, 0.05, 0.9, 0.7], [0.35, 0.47, 0.5, 0.56]]])
- img_data = tf.image.decode_jpeg(image_raw_data)
- # sample_distorted_bounding_box 要求输入图片必须是实数类型.
- image_float = tf.image.convert_image_dtype(img_data, tf.float32)
- begin, size, bbox_for_draw = tf.image.sample_distorted_bounding_box(
- tf.shape(image_float), bounding_boxes=boxes, min_object_covered=0.4) # 截取部分至少包含某个标注框 40% 的内容
- # 截取后的图片
- distorted_image = tf.slice(image_float, begin, size) # 这是截取的操作
- plt.imshow(distorted_image.eval())
- plt.show()
- # 在原图上用标注框画出截取的范围. 由于原图的分辨率较大 (2673x1797), 生成的标注框
- # 在 Jupyter Notebook 上通常因边框过细而无法分辨, 这里为了演示方便先缩小分辨率.
- image_small = tf.image.resize_images(image_float, [180, 267], method=0)
- batchced_img = tf.expand_dims(image_small, 0)
- image_with_box = tf.image.draw_bounding_boxes(batchced_img, bbox_for_draw)
- print(bbox_for_draw.eval())
- plt.imshow(image_with_box[0].eval())
- plt.show()
来源: http://www.bubuko.com/infodetail-3229475.html